In this course, you will learn the science behind how digital images and video are made, altered, stored, and used. We will look at the vast world of digital imaging, from how computers and digital cameras form images to how digital special effects are used in Hollywood movies to how the Mars Rover was able to send photographs across millions of miles of space. The course starts by looking at how the human visual system works and then teaches you about the engineering, mathematics, and computer science that makes digital images work. You will learn the basic algorithms used for adjusting images, explore JPEG and MPEG standards for encoding and compressing video images, and go on to learn about image segmentation, noise removal and filtering. Finally, we will end with image processing techniques used in medicine. This course consists of 7 basic modules and 2 bonus (non-graded) modules. There are optional MATLAB exercises; learners will have access to MATLAB Online for the course duration. Each module is independent, so you can follow your interests.
11 - Derivatives, Laplacian & Unsharp masking - Duration 14:24 - Optional breaks at 05:21 and 11:33
Skills You'll Learn
Image Processing, Image Compression, Image Restoration, Image Segmentation
Reviews
This is an excellent course for understanding a lot of details on Image Processing. After this course, the more you apply the techniques learned, the more you make progress in the research field.
It is a great course that the professor teaches very patiently. The knowledge is very advanced that we can use them in our daily work and projects. Thanks , professor and Duke.Thanks, coursera.
Some of the most basic tools in image processing, like median filtering and histogram equalization, are still among the most powerful. We will describe these and provide a modern interpretation of these basic tools. Students will then become familiar with simple and still popular approaches. We will also include non-local means, a more modern technique that still uses classical tools.
Taught By
Guillermo Sapiro
Professor
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